APLIKASI SISTEM PAKAR UNTUK MENDIAGNOSA LEBIH DINI PENYAKIT KOLERA PADA ANAK MENGGUNAKAN METODE K-NEAREST NEIGHBOR (KNN)

Cholera is a disease that can be dangerous if not treated immediately. The main symptoms are diarrhea, shock, and seizures. Children with cholera need serious treatment from medical personnel. The problem that often occurs is that there are not many doctors who are experts in this field, plus for people who are far from urban areas such as people who live in mountainous areas or remote villages it is very unlikely to be able to consult a doctor due to distance, cost and time factors. This study aims to build an expert system application that is able to diagnose cholera in children early by applying the K-Nearest Neighbor (KNN) method, so that people, especially those who are far from urban areas, can find out more about cholera in children so that it can be treated more quickly. The KNN method can be implemented in a system that adopts the ability of experts to diagnose cholera in children. In applying the KNN method, symptom initialization is carried out by entering the density value and looking for the combination confidence value to get the diagnostic result. From this research, it can be concluded that the application that was built can be used to replace experts in helping to diagnose cholera in children early.